bims-mascan 2023-10-01 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2023–10–01
eightteen papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

Exploring the Impact of Organic Solvent Quality and Unusual Adduct Formation during LC-MS-Based Lipidomic Profiling.
Pyruvate Kinase Activity Regulates Cystine Starvation Induced Ferroptosis through Malic Enzyme 1 in Pancreatic Cancer Cells.
Integrated proteomic and phosphoproteomic data-independent acquisition data evaluate the personalized drug responses of primary and metastatic tumors in colorectal cancer.
omicsMIC: a Comprehensive Benchmarking Platform for Robust Comparison of Imputation Methods in Mass Spectrometry-based Omics Data.
Recent advances in mass spectrometry-based proteomics and metabolomics in chronic rhinosinusitis with nasal polyps.
Computational Analysis of Plasma Lipidomics from Mice Fed Standard Chow and Ketogenic Diet.
Exploiting ion-mobility mass spectrometry for unraveling proteome complexity.
Defining the glucosylceramide population of C. elegans.
ShinyMetID: An R shiny package for metabolite identification by mass spectral matching.
Quality Control in Targeted GC-MS for Amino Acid-OMICS.
Comprehensive Metabolomic Analysis of Human Heart Tissue Enabled by Parallel Metabolite Extraction and High-Resolution Mass Spectrometry.
Toward a Unifying Hypothesis for Redesigned Lipid Catabolism as a Clinical Target in Advanced, Treatment-Resistant Carcinomas.
Meta-Analysis of COVID-19 Metabolomics Identifies Variations in Robustness of Biomarkers.
Evaluation of Lipid Extraction Protocols for Untargeted Analysis of Mouse Tissue Lipidome.
A basic phosphoproteomic-DIA workflow integrating precise quantification of phosphosites in systems biology.
Proteomics protocol for obtaining extracellular vesicle from human plasma using asymmetrical flow field-flow fractionation technology.
Orbitrap Mass Spectrometry and High-Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Enable the in-Depth Analysis of Human Serum Proteoforms.
Acidic Methanol Treatment Facilitates Matrix-Assisted Laser Desorption Ionization-Mass Spectrometry Imaging of Energy Metabolism.

Metabolites. 2023 Aug 22. pii: 966. [Epub ahead of print]13(9):

Exploring the Impact of Organic Solvent Quality and Unusual Adduct Formation during LC-MS-Based Lipidomic Profiling.

Tomas Cajka, Jiri Hricko, Lucie Rudl Kulhava, Michaela Paucova, Michaela Novakova, Oliver Fiehn, Ondrej Kuda.

  Liquid chromatography-mass spectrometry (LC-MS) is the key technique for analyzing complex lipids in biological samples. Various LC-MS modes are used for lipid separation, including different stationary phases, mobile-phase solvents, and modifiers. Quality control in lipidomics analysis is crucial to ensuring the generated data's reliability, reproducibility, and accuracy. While several quality control measures are commonly discussed, the impact of organic solvent quality during LC-MS analysis is often overlooked. Additionally, the annotation of complex lipids remains prone to biases, leading to potential misidentifications and incomplete characterization of lipid species. In this study, we investigate how LC-MS-grade isopropanol from different vendors may influence the quality of the mobile phase used in LC-MS-based untargeted lipidomic profiling of biological samples. Furthermore, we report the occurrence of an unusual, yet highly abundant, ethylamine adduct [M+46.0651]+ that may form for specific lipid subclasses during LC-MS analysis in positive electrospray ionization mode when acetonitrile is part of the mobile phase, potentially leading to lipid misidentification. These findings emphasize the importance of considering solvent quality in LC-MS analysis and highlight challenges in lipid annotation.

Keywords:  MS/MS annotation; adduct formation; lipidomics; lipids; liquid chromatography; mass spectrometry; metabolomics; method development; misidentification; solvent quality

DOI:  https://doi.org/10.3390/metabo13090966
bioRxiv. 2023 Sep 17. pii: 2023.09.15.557984. [Epub ahead of print]

Pyruvate Kinase Activity Regulates Cystine Starvation Induced Ferroptosis through Malic Enzyme 1 in Pancreatic Cancer Cells.

Elliot Ensink, Tessa Jordan, Hyllana C D Medeiros, Galloway Thurston, Anmol Pardal, Lei Yu, Sophia Y Lunt.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with high mortality and limited efficacious therapeutic options. PDAC cells undergo metabolic alterations to survive within a nutrient-depleted tumor microenvironment. One critical metabolic shift in PDAC cells occurs through altered isoform expression of the glycolytic enzyme, pyruvate kinase (PK). Pancreatic cancer cells preferentially upregulate pyruvate kinase muscle isoform 2 isoform (PKM2). PKM2 expression reprograms many metabolic pathways, but little is known about its impact on cystine metabolism. Cystine metabolism is critical for supporting survival through its role in defense against ferroptosis, a non-apoptotic iron-dependent form of cell death characterized by unchecked lipid peroxidation. To improve our understanding of the role of PKM2 in cystine metabolism and ferroptosis in PDAC, we generated PKM2 knockout (KO) human PDAC cells. Fascinatingly, PKM2KO cells demonstrate a remarkable resistance to cystine starvation mediated ferroptosis. This resistance to ferroptosis is caused by decreased PK activity, rather than an isoform-specific effect. We further utilized stable isotope tracing to evaluate the impact of glucose and glutamine reprogramming in PKM2KO cells. PKM2KO cells depend on glutamine metabolism to support antioxidant defenses against lipid peroxidation, primarily by increased glutamine flux through the malate aspartate shuttle and utilization of ME1 to produce NADPH. Ferroptosis can be synergistically induced by the combination of PKM2 activation and inhibition of the cystine/glutamate antiporter in vitro . Proof-of-concept in vivo experiments demonstrate the efficacy of this mechanism as a novel treatment strategy for PDAC.
Highlights: PKM2KO in pancreatic ductal adenocarcinoma (PDAC) cells produces enhanced defense against cystine starvation induced ferroptosis.Pharmacologic activation of pyruvate kinase (PK) activity promotes ferroptosis under cystine starvation, while inhibition promotes ferroptosis survival in PDAC cells.Decrease in PK activity reprograms glutamine metabolism to increase use of malic enzyme 1 and promote survival under cystine starvation in PDAC cells. Cystine starvation and activation of pyruvate kinase synergistically decreases progression of pancreatic cancer in vivo .

DOI: https://doi.org/10.1101/2023.09.15.557984
Biophys Rep. 2023 Apr 30. 9(2): 67-81

Integrated proteomic and phosphoproteomic data-independent acquisition data evaluate the personalized drug responses of primary and metastatic tumors in colorectal cancer.

Xumiao Li, Yiming Huang, Kuo Zheng, Guanyu Yu, Qinqin Wang, Lei Gu, Jingquan Li, Hui Wang, Wei Zhang, Yidi Sun, Chen Li.

  Mass spectrometry (MS)-based proteomics and phosphoproteomics are powerful methods to study the biological mechanisms, diagnostic biomarkers, prognostic analysis, and drug therapy of tumors. Data-independent acquisition (DIA) mode is considered to perform better than data-dependent acquisition (DDA) mode in terms of quantitative reproducibility, specificity, accuracy, and identification of low-abundance proteins. Mini patient derived xenograft (MiniPDX) model is an effective model to assess the response to antineoplastic drugs in vivo and is helpful for the precise treatment of cancer patients. Kinases are favorable spots for tumor-targeted drugs, and their functional completion relies on signaling pathways through phosphorylating downstream substrates. Kinase-phosphorylation networks or edge interactions are considered more credible and permanent for characterizing complex diseases. Here, we provide a workflow for personalized drug response assessment in primary and metastatic colorectal cancer (CRC) tumors using DIA proteomic data, DIA phosphoproteomic data, and MiniPDX models. Three kinase inhibitors, afatinib, gefitinib, and regorafenib, are tested pharmacologically. The process mainly includes the following steps: clinical tissue collection, sample preparation, hybrid spectral libraries establishment, MS data acquisition, kinase-substrate network construction, in vivo drug test, and elastic regression modeling. Our protocol gives a more direct data basis for individual drug responses, and will improve the selection of treatment strategies for patients without the druggable mutation.

Keywords:  Data-independent acquisition (DIA); Kinase-substrate network; Mini patient derived xenograft (MiniPDX); Personalized drug responses; Phosphoproteomics; Proteomics

DOI:  https://doi.org/10.52601/bpr.2022.210048
bioRxiv. 2023 Sep 15. pii: 2023.09.12.557189. [Epub ahead of print]

omicsMIC: a Comprehensive Benchmarking Platform for Robust Comparison of Imputation Methods in Mass Spectrometry-based Omics Data.

Weiqiang Lin, Jiadong Ji, Kuan-Jui Su, Chuan Qiu, Qing Tian, Lan-Juan Zhao, Zhe Luo, Hui Shen, Chong Wu, Hongwen Deng.

Mass spectrometry is a powerful and widely used tool for generating proteomics, lipidomics, and metabolomics profiles, which is pivotal for elucidating biological processes and identifying biomarkers. However, missing values in spectrometry-based omics data may pose a critical challenge for the comprehensive identification of biomarkers and elucidation of the biological processes underlying human complex disorders. To alleviate this issue, various imputation methods for mass spectrometry-based omics data have been developed. However, a comprehensive and systematic comparison of these imputation methods is still lacking, and researchers are frequently confronted with a multitude of options without a clear rationale for method selection. To address this pressing need, we developed omicsMIC (mass spectrometrybased omics with Missing values Imputation methods Comparison platform), an interactive platform that provides researchers with a versatile framework to simulate and evaluate the performance of 28 diverse imputation methods. omicsMIC offers a nuanced perspective, acknowledging the inherent heterogeneity in biological data and the unique attributes of each dataset. Our platform empowers researchers to make data-driven decisions in imputation method selection based on real-time visualizations of the outcomes associated with different imputation strategies. The comprehensive benchmarking and versatility of omicsMIC make it a valuable tool for the scientific community engaged in mass spectrometry-based omics research. OmicsMIC is freely available at https://github.com/WQLin8/omicsMIC .

DOI: https://doi.org/10.1101/2023.09.12.557189
Front Immunol. 2023 ;14 1267194

Recent advances in mass spectrometry-based proteomics and metabolomics in chronic rhinosinusitis with nasal polyps.

Shudi Guo, Ming Tian, Yunping Fan, Xiangyang Zhang.

  Chronic rhinosinusitis with nasal polyps (CRSwNP) is a complex and heterogeneous disease, typically diagnosed through endoscopy and computed tomography and treated with glucocorticoid or surgery. There is an urgent need to develop molecular-level diagnostic or prognostic tools to better understand the pathophysiology of CRSwNP. Proteomics and metabolomics, emerging fields, offer significant potential in elucidating the mechanisms underlying CRSwNP. Mass spectrometry, a powerful and sensitive tool for trace substance detection, is broadly applied for proteomics and metabolomics analysis in CRSwNP research. While previous literature has summarized the advancement of mass spectrometry-based CRSwNP proteomics from 2004 to 2018, recent years have seen new advances in this field, particularly about non-invasive samples and exosomes. Furthermore, mass spectrometry-based CRSwNP metabolomics research has opened new avenues for inquiry. Therefore, we present a comprehensive review of mass spectrometry-based proteomics and metabolomics studies on CRSwNP conducted between 2019 and 2022. Specifically, we highlight protein and metabolic biomarkers that have been utilized as diagnostic or prognostic markers for CRSwNP. Lastly, we conclude with potential directions for future mass spectrometry-based omics studies of CRSwNP.

Keywords:  biomarker; chronic rhinosinusitis; mass spectrometry; metabolomics; proteomics

DOI:  https://doi.org/10.3389/fimmu.2023.1267194
Bio Protoc. 2023 Sep 20. 13(18): e4819

Computational Analysis of Plasma Lipidomics from Mice Fed Standard Chow and Ketogenic Diet.

Amy L Seufert, James W Hickman, Jaewoo Choi, Brooke A Napier.

  Dietary saturated fatty acids (SFAs) are upregulated in the blood circulation following digestion. A variety of circulating lipid species have been implicated in metabolic and inflammatory diseases; however, due to the extreme variability in serum or plasma lipid concentrations found in human studies, established reference ranges are still lacking, in addition to lipid specificity and diagnostic biomarkers. Mass spectrometry is widely used for identification of lipid species in the plasma, and there are many differences in sample extraction methods within the literature. We used ultra-high performance liquid chromatography (UPLC) coupled to a high-resolution hybrid triple quadrupole-time-of-flight (QToF) mass spectrometry (MS) to compare relative peak abundance of specific lipid species within the following lipid classes: free fatty acids (FFAs), triglycerides (TAGs), phosphatidylcholines (PCs), and sphingolipids (SGs), in the plasma of mice fed a standard chow (SC; low in SFAs) or ketogenic diet (KD; high in SFAs) for two weeks. In this protocol, we used Principal Component Analysis (PCA) and R to visualize how individual mice clustered together according to their diet, and we found that KD-fed mice displayed unique blood profiles for many lipid species identified within each lipid class compared to SC-fed mice. We conclude that two weeks of KD feeding is sufficient to significantly alter circulating lipids, with PCs being the most altered lipid class, followed by SGs, TAGs, and FFAs, including palmitic acid (PA) and PA-saturated lipids. This protocol is needed to advance knowledge on the impact that SFA-enriched diets have on concentrations of specific lipids in the blood that are known to be associated with metabolic and inflammatory diseases. Key features • Analysis of relative plasma lipid concentrations from mice on different diets using R. • Lipidomics data collected via ultra-high performance liquid chromatography (UPLC) coupled to a high-resolution hybrid triple quadrupole-time-of-flight (QToF) mass spectrometry (MS). • Allows for a comprehensive comparison of diet-dependent plasma lipid profiles, including a variety of specific lipid species within several different lipid classes. • Accumulation of certain free fatty acids, phosphatidylcholines, triglycerides, and sphingolipids are associated with metabolic and inflammatory diseases, and plasma concentrations may be clinically useful.

Keywords:  Circulating lipids; Free fatty acids; Ketogenic diet; Lipidomics; Mass spectrometry; Phosphatidylcholines; Sphingolipids; Triglycerides

DOI:  https://doi.org/10.21769/BioProtoc.4819
J Sep Sci. 2023 Sep;46(18): e2300512

Exploiting ion-mobility mass spectrometry for unraveling proteome complexity.

Stan Perchepied, Zhuoheng Zhou, Goran Mitulović, Sebastiaan Eeltink.

  Ion mobility spectrometry-mass spectrometry (IMS-MS) is experiencing rapid growth in proteomic studies, driven by its enhancements in dynamic range and throughput, increasing the quantitation precision, and the depth of proteome coverage. The core principle of ion mobility spectrometry is to separate ions in an inert gas under the influence of an electric field based on differences in drift time. This minireview provides an introduction to IMS operation modes and a description of advantages and limitations is presented. Moreover, the principles of trapped IMS-MS (TIMS-MS), including parallel accumulation-serial fragmentation are discussed. Finally, emerging applications linked to TIMS focusing on sample throughput (in clinical proteomics) and sensitivity (single-cell proteomics) are reviewed, and the possibilities of intact protein analysis are discussed.

Keywords:  TIMS-TOF; clinical proteomics; data-independent acquisition; parallel accumulation-serial fragmentation; single-cell analysis

DOI:  https://doi.org/10.1002/jssc.202300512
Front Physiol. 2023 ;14 1244158

Defining the glucosylceramide population of C. elegans.

Mark A Xatse, Carissa Perez Olsen.

  Glucosylceramides (GlcCer) are lipids that impact signaling pathways, serve as critical components of cellular membranes, and act as precursors for hundreds of other complex glycolipid species. Abnormal GlcCer metabolism is linked to many diseases, including cancers, diabetes, Gaucher disease, neurological disorders, and skin disorders. A key hurdle to fully understanding the role of GlcCer in disease is the development of methods to accurately detect and quantify these lipid species in a model organism. This will allow for the dissection of the role of this pool in vivo with a focus on all the individual types of GlcCer. In this review, we will discuss the analysis of the GlcCer population specifically in the nematode Caenorhabditis elegans, focusing on the mass spectrometry-based methods available for GlcCer quantification. We will also consider the combination of these approaches with genetic interrogation of GlcCer metabolic genes to define the biological role of these unique lipids. Furthermore, we will explore the implications and obstacles for future research.

Keywords:  C. elegans; glucosylceramide (GlcCer); lipidomic analysis; mass spectrometry; sphingolipid

DOI:  https://doi.org/10.3389/fphys.2023.1244158
Chemometr Intell Lab Syst. 2023 Sep 15. pii: 104861. [Epub ahead of print]240

ShinyMetID: An R shiny package for metabolite identification by mass spectral matching.

Youngjae Oh, Shinjune Kim, Seongho Kim, Jaesik Jeong.

  We present metabolite identification software in the form of R Shiny. Metabolite identification by mass spectral matching in gas chromatography (GC-MS)-based untargeted metabolomics can be done by using the easy-to-use software. Various similarity measures are given and toy example using graphical user interface is presented.

Keywords:  GC-MS; LC-MS; Mass spectral matching; Metabolite identification

DOI:  https://doi.org/10.1016/j.chemolab.2023.104861
Metabolites. 2023 Aug 31. pii: 986. [Epub ahead of print]13(9):

Quality Control in Targeted GC-MS for Amino Acid-OMICS.

Dimitrios Tsikas, Bibiana Beckmann.

  Gas chromatography-mass spectrometry (GC-MS) is suitable for the analysis of non-polar analytes. Free amino acids (AA) are polar, zwitterionic, non-volatile and thermally labile analytes. Chemical derivatization of AA is indispensable for their measurement by GC-MS. Specific conversion of AA to their unlabeled methyl esters (d0Me) using 2 M HCl in methanol (CH3OH) is a suitable derivatization procedure (60 min, 80 °C). Performance of this reaction in 2 M HCl in tetradeutero-methanol (CD3OD) generates deuterated methyl esters (d3Me) of AA, which can be used as internal standards in GC-MS. d0Me-AA and d3Me-AA require subsequent conversion to their pentafluoropropionyl (PFP) derivatives for GC-MS analysis using pentafluoropropionic anhydride (PFPA) in ethyl acetate (30 min, 65 °C). d0Me-AA-PFP and d3Me-AA-PFP derivatives of AA are readily extractable into water-immiscible, GC-compatible organic solvents such as toluene. d0Me-AA-PFP and d3Me-AA-PFP derivatives are stable in toluene extracts for several weeks, thus enabling high throughput quantitative measurement of biological AA by GC-MS using in situ prepared d3Me-AA as internal standards in OMICS format. Here, we describe the development of a novel OMICS-compatible QC system and demonstrate its utility for the quality control of quantitative analysis of 21 free AA and metabolites in human plasma samples by GC-MS as Me-PFP derivatives. The QC system involves cross-standardization of the concentrations of the AA in their aqueous solutions at four concentration levels and a quantitative control of AA at the same four concentration levels in pooled human plasma samples. The retention time (tR)-based isotope effects (IE) and the difference (δ(H/D) of the retention times of the d0Me-AA-PFP derivatives (tR(H)) and the d3Me-AA-PFP derivatives (tR(D)) were determined in study human plasma samples of a nutritional study (n = 353) and in co-processed QC human plasma samples (n = 64). In total, more than 400 plasma samples were measured in eight runs in seven working days performed by a single person. The proposed QC system provides information about the quantitative performance of the GC-MS analysis of AA in human plasma. IE, δ(H/D) and a massive drop of the peak area values of the d3Me-AA-PFP derivatives may be suitable as additional parameters of qualitative analysis in targeted GC-MS amino acid-OMICS.

Keywords:  OMICS; amino acids; metabolites; plasma; quality control; sample preparation

DOI:  https://doi.org/10.3390/metabo13090986
bioRxiv. 2023 Sep 16. pii: 2023.09.15.558013. [Epub ahead of print]

Comprehensive Metabolomic Analysis of Human Heart Tissue Enabled by Parallel Metabolite Extraction and High-Resolution Mass Spectrometry.

Benjamin Wancewicz, Melissa R Pergande, Yanlong Zhu, Zhan Gao, Zhuoxin Shi, Kylie Plouff, Ying Ge.

The heart contracts incessantly and requires a constant supply of energy, utilizing numerous metabolic substrates such as fatty acids, carbohydrates, lipids, and amino acids to supply its high energy demands. Therefore, a comprehensive analysis of various metabolites is urgently needed for understanding cardiac metabolism; however, complete metabolome analyses remain challenging due to the broad range of metabolite polarities which makes extraction and detection difficult. Herein, we implemented parallel metabolite extractions and high-resolution mass spectrometry (MS)-based methods to obtain a comprehensive analysis of the human heart metabolome. To capture the diverse range of metabolite polarities, we first performed six parallel liquid-liquid extractions (three monophasic, two biphasic, and one triphasic extractions) of healthy human donor heart tissue. Next, we utilized two complementary MS platforms for metabolite detection - direct-infusion ultrahigh-resolution Fourier-transform ion cyclotron resonance (DI-FTICR) and high-resolution liquid chromatography quadrupole time-of-flight tandem MS (LC-Q-TOF MS/MS). Using DI-FTICR MS, 9,521 metabolic features were detected where 7,699 were assigned a chemical formula and 1,756 were assigned an annotated by accurate mass assignment. Using LC-Q-TOF MS/MS, 21,428 metabolic features were detected where 626 metabolites were identified based on fragmentation matching against publicly available libraries. Collectively, 2276 heart metabolites were identified in this study which span a wide range of polarities including polar (benzenoids, alkaloids and derivatives and nucleosides) as well as non-polar (phosphatidylcholines, acylcarnitines, and fatty acids) compounds. The results of this study will provide critical knowledge regarding the selection of appropriate extraction and MS detection methods for the analysis of the diverse classes of human heart metabolites.
Table of Contents Graphical Abstract:

DOI: https://doi.org/10.1101/2023.09.15.558013
Int J Mol Sci. 2023 Sep 21. pii: 14365. [Epub ahead of print]24(18):

Toward a Unifying Hypothesis for Redesigned Lipid Catabolism as a Clinical Target in Advanced, Treatment-Resistant Carcinomas.

Paul M Bingham, Zuzana Zachar.

  We review extensive progress from the cancer metabolism community in understanding the specific properties of lipid metabolism as it is redesigned in advanced carcinomas. This redesigned lipid metabolism allows affected carcinomas to make enhanced catabolic use of lipids in ways that are regulated by oxygen availability and is implicated as a primary source of resistance to diverse treatment approaches. This oxygen control permits lipid catabolism to be an effective energy/reducing potential source under the relatively hypoxic conditions of the carcinoma microenvironment and to do so without intolerable redox side effects. The resulting robust access to energy and reduced potential apparently allow carcinoma cells to better survive and recover from therapeutic trauma. We surveyed the essential features of this advanced carcinoma-specific lipid catabolism in the context of treatment resistance and explored a provisional unifying hypothesis. This hypothesis is robustly supported by substantial preclinical and clinical evidence. This approach identifies plausible routes to the clinical targeting of many or most sources of carcinoma treatment resistance, including the application of existing FDA-approved agents.

Keywords:  CPI-613; cancer; crizotinib; fatty acid; lipid; metabolism; resistance; thioridazine

DOI:  https://doi.org/10.3390/ijms241814365
Int J Mol Sci. 2023 Sep 21. pii: 14371. [Epub ahead of print]24(18):

Meta-Analysis of COVID-19 Metabolomics Identifies Variations in Robustness of Biomarkers.

Anthony Onoja, Johanna von Gerichten, Holly-May Lewis, Melanie J Bailey, Debra J Skene, Nophar Geifman, Matt Spick.

  The global COVID-19 pandemic resulted in widespread harms but also rapid advances in vaccine development, diagnostic testing, and treatment. As the disease moves to endemic status, the need to identify characteristic biomarkers of the disease for diagnostics or therapeutics has lessened, but lessons can still be learned to inform biomarker research in dealing with future pathogens. In this work, we test five sets of research-derived biomarkers against an independent targeted and quantitative Liquid Chromatography-Mass Spectrometry metabolomics dataset to evaluate how robustly these proposed panels would distinguish between COVID-19-positive and negative patients in a hospital setting. We further evaluate a crowdsourced panel comprising the COVID-19 metabolomics biomarkers most commonly mentioned in the literature between 2020 and 2023. The best-performing panel in the independent dataset-measured by F1 score (0.76) and AUROC (0.77)-included nine biomarkers: lactic acid, glutamate, aspartate, phenylalanine, β-alanine, ornithine, arachidonic acid, choline, and hypoxanthine. Panels comprising fewer metabolites performed less well, showing weaker statistical significance in the independent cohort than originally reported in their respective discovery studies. Whilst the studies reviewed here were small and may be subject to confounders, it is desirable that biomarker panels be resilient across cohorts if they are to find use in the clinic, highlighting the importance of assessing the robustness and reproducibility of metabolomics analyses in independent populations.

Keywords:  COVID-19; biomarkers; diagnostics; future pandemics; machine learning; mass spectrometry; metabolomics; validation

DOI:  https://doi.org/10.3390/ijms241814371
Metabolites. 2023 Sep 09. pii: 1002. [Epub ahead of print]13(9):

Evaluation of Lipid Extraction Protocols for Untargeted Analysis of Mouse Tissue Lipidome.

Ashraf M Omar, Qibin Zhang.

  Lipidomics refers to the full characterization of lipids present within a cell, tissue, organism, or biological system. One of the bottlenecks affecting reliable lipidomic analysis is the extraction of lipids from biological samples. An ideal extraction method should have a maximum lipid recovery and the ability to extract a broad range of lipid classes with acceptable reproducibility. The most common lipid extraction relies on either protein precipitation (monophasic methods) or liquid-liquid partitioning (bi- or triphasic methods). In this study, three monophasic extraction systems, isopropanol (IPA), MeOH/MTBE/CHCl3 (MMC), and EtOAc/EtOH (EE), alongside three biphasic extraction methods, Folch, butanol/MeOH/heptane/EtOAc (BUME), and MeOH/MTBE (MTBE), were evaluated for their performance in characterization of the mouse lipidome of six different tissue types, including pancreas, spleen, liver, brain, small intestine, and plasma. Sixteen lipid classes were investigated in this study using reversed-phase liquid chromatography/mass spectrometry. Results showed that all extraction methods had comparable recoveries for all tested lipid classes except lysophosphatidylcholines, lysophosphatidylethanolamines, acyl carnitines, sphingomyelines, and sphingosines. The recoveries of these classes were significantly lower with the MTBE method, which could be compensated by the addition of stable isotope-labeled internal standards prior to lipid extraction. Moreover, IPA and EE methods showed poor reproducibility in extracting lipids from most tested tissues. In general, Folch is the optimum method in terms of efficacy and reproducibility for extracting mouse pancreas, spleen, brain, and plasma. However, MMC and BUME methods are more favored when extracting mouse liver or intestine.

Keywords:  UHPLC-HRMS; lipid extraction; mouse lipidome; mouse tissue; untargeted lipidomics

DOI:  https://doi.org/10.3390/metabo13091002
Biophys Rep. 2023 Apr 30. 9(2): 82-98

A basic phosphoproteomic-DIA workflow integrating precise quantification of phosphosites in systems biology.

Yi Di, Wenxue Li, Barbora Salovska, Qian Ba, Zhenyi Hu, Shisheng Wang, Yansheng Liu.

  Phosphorylation is one of the most important post-translational modifications (PTMs) of proteins, governing critical protein functions. Most human proteins have been shown to undergo phosphorylation, and phosphoproteomic studies have been widely applied due to recent advancements in high-resolution mass spectrometry technology. Although the experimental workflow for phosphoproteomics has been well-established, it would be useful to optimize and summarize a detailed, feasible protocol that combines phosphoproteomics and data-independent acquisition (DIA), along with follow-up data analysis procedures due to the recent instrumental and bioinformatic advances in measuring and understanding tens of thousands of site-specific phosphorylation events in a single experiment. Here, we describe an optimized Phos-DIA protocol, from sample preparation to bioinformatic analysis, along with practical considerations and experimental configurations for each step. The protocol is designed to be robust and applicable for both small-scale phosphoproteomic analysis and large-scale quantification of hundreds of samples for studies in systems biology and systems medicine.

Keywords:  Bioinformatic analysis; High-resolution mass spectrometry technology; Phosphoproteomics; Systems biology; Systems medicine

DOI:  https://doi.org/10.52601/bpr.2023.230007
STAR Protoc. 2023 Sep 23. pii: S2666-1667(23)00482-3. [Epub ahead of print]4(4): 102515

Proteomics protocol for obtaining extracellular vesicle from human plasma using asymmetrical flow field-flow fractionation technology.

Na Li, Yumeng Yan, Bowen Wu, Jifeng Wang, Fuquan Yang.

  Plasma extracellular vesicles (EVs) represent a potential resource for biomarkers of multiple diseases. Here, we present a protocol for obtaining EVs from human plasma using asymmetrical flow field-flow fractionation technology. We describe steps for using tandem mass tags to perform comparative proteomic studies of a large clinical cohort. We then detail targeted quantitative analysis of differential proteins based on a parallel reaction monitoring technique. For complete details on the use and execution of this protocol, please refer to Wu et al. (2020)1 and Li et al. (2023).2.

Keywords:  Cell Biology; Cell Isolation; Cell Separation/Fractionation; Clinical Protocol; Health Sciences; Mass Spectrometry; Molecular/Chemical Probes; Protein Expression and Purification; Proteomics

DOI:  https://doi.org/10.1016/j.xpro.2023.102515
J Proteome Res. 2023 Sep 29.

Orbitrap Mass Spectrometry and High-Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Enable the in-Depth Analysis of Human Serum Proteoforms.

Jake T Kline, Michael W Belford, Cornelia L Boeser, Romain Huguet, Ryan T Fellers, Joseph B Greer, Sylvester M Greer, David M Horn, Kenneth R Durbin, Jean-Jacques Dunyach, Nagib Ahsan, Luca Fornelli.

  Blood serum and plasma are arguably the most commonly analyzed clinical samples, with dozens of proteins serving as validated biomarkers for various human diseases. Top-down proteomics may provide additional insights into disease etiopathogenesis since this approach focuses on protein forms, or proteoforms, originally circulating in blood, potentially providing access to information about relevant post-translational modifications, truncations, single amino acid substitutions, and many other sources of protein variation. However, the vast majority of proteomic studies on serum and plasma are carried out using peptide-centric, bottom-up approaches that cannot recapitulate the original proteoform content of samples. Clinical laboratories have been slow to adopt top-down analysis, also due to higher sample handling requirements. In this study, we describe a straightforward protocol for intact proteoform sample preparation based on the depletion of albumin and immunoglobulins, followed by simplified protein fractionation via polyacrylamide gel electrophoresis. After molecular weight-based fractionation, we supplemented the traditional liquid chromatography-tandem mass spectrometry (LC-MS2) data acquisition with high-field asymmetric waveform ion mobility spectrometry (FAIMS) to further simplify serum proteoform mixtures. This LC-FAIMS-MS2 method led to the identification of over 1000 serum proteoforms < 30 kDa, outperforming traditional LC-MS2 data acquisition and more than doubling the number of proteoforms identified in previous studies.

Keywords:  FAIMS; Orbitrap; PEPPI; Protein depletion; biomarkers; blood; mass spectrometry; proteoform; serum; top-down proteomics

DOI:  https://doi.org/10.1021/acs.jproteome.3c00488
Anal Chem. 2023 Sep 27.

Acidic Methanol Treatment Facilitates Matrix-Assisted Laser Desorption Ionization-Mass Spectrometry Imaging of Energy Metabolism.

Wenyun Lu, Noel R Park, Tara TeSlaa, Connor S R Jankowski, Laith Samarah, Melanie McReynolds, Xi Xing, Jessica Schembri, Morgan T Woolf, Joshua D Rabinowitz, Shawn M Davidson.

Detection of small molecule metabolites (SMM), particularly those involved in energy metabolism using MALDI-mass spectrometry imaging (MSI), is challenging due to factors including ion suppression from other analytes present (e.g., proteins and lipids). One potential solution to enhance SMM detection is to remove analytes that cause ion suppression from tissue sections before matrix deposition through solvent washes. Here, we systematically investigated solvent treatment conditions to improve SMM signal and preserve metabolite localization. Washing with acidic methanol significantly enhances the detection of phosphate-containing metabolites involved in energy metabolism. The improved detection is due to removing lipids and highly polar metabolites that cause ion suppression and denaturing proteins that release bound phosphate-containing metabolites. Stable isotope infusions of [13C6]nicotinamide coupled to MALDI-MSI ("Iso-imaging") in the kidney reveal patterns that indicate blood vessels, medulla, outer stripe, and cortex. We also observed different ATP:ADP raw signals across mouse kidney regions, consistent with regional differences in glucose metabolism favoring either gluconeogenesis or glycolysis. In mouse muscle, Iso-imaging using [13C6]glucose shows high glycolytic flux from infused circulating glucose in type 1 and 2a fibers (soleus) and relatively lower glycolytic flux in type 2b fiber type (gastrocnemius). Thus, improved detection of phosphate-containing metabolites due to acidic methanol treatment combined with isotope tracing provides an improved way to probe energy metabolism with spatial resolution in vivo.

DOI: https://doi.org/10.1021/acs.analchem.3c01875